本章有意将生成式人工智能及其狭义的人工智能兄弟姐妹与通用人工智能区分开来,后者被赋予了许多名称来描述人造机器发展意识的时刻。本章提出创意人员区分两者,以便您可以更好地协调与生成式人工智能交互的利弊。针对任何人工智能的警示故事和消极情绪也可以被扭转,从而激活我们的创造力。我们从许多艺术家和极具创造力的个人的作品中看到了这一点,他们天生抵制顺从,将消极情绪转化为积极的善意力量,并渴望改善地球的存在。
This chapter intentionally separates generative AI and its narrow AI siblings from Artificial General Intelligence, which has been given many names describing a moment in time where a human-made machine develops consciousness. The chapter proposes that creatives differentiate between the two so that you can better reconcile the pros and cons of interacting with generative AI. The cautionary tales and negativity directed toward any AI can also be turned around activating our creativity. We see this from the work of many artists and highly creative individuals who innately resist conformity, transform negativity into positive forces for good, and desire to improve planetary existence.
区分狭义人工智能和通用人工智能
Differentiating Between Narrow and General AI
天塌下来了。
The sky is falling.
这句出自《小鸡非凡故事》的著名引言在当今时代引起了共鸣,当时人们对狭隘人工智能工具、机器学习模型、神经网络及其深度学习基础的反动反应是谨慎和反乌托邦的。例如,奇点的核心前提是,它将标志着一个自主、自我递归、自我改进的人工智能将超越人类能力和认知智能的时间点,从而导致一个超越人类的技术快速增长时期。理解或控制的能力。我们鼓励感兴趣的创意人员深入研究围绕智能定义、机器除解决问题之外的认知能力、自主人工智能代理的构成等方面的争论。
This famous quote from the Remarkable Story of Chicken Little resonates at a time where reactionary responses to narrow AI tools, their machine learning models, neural networks, and their deep learning foundations are cautionary and dystopian. For example, the central premise of the singularity is that it would mark a point in time where an autonomous, self-recursive, self-improving AI would surpass human capabilities and cognitive intelligence, leading to a period of rapid technological growth that is beyond human capacity to comprehend or control. Interested creatives are encouraged to deepen their research of the debates that swirl around definitions of intelligence, cognitive capabilities of machines beyond problem-solving, what constitutes an autonomous AI agent, and more.
作者:用幽默的方式来说:这些超级智能机器将能够递归地自我改进,在设计和建造连续几代日益强大的机器时不断变得更好更快,从而产生失控效应。
Author: Say this in a humorous way: These superintelligent machines would be capable of recursive self-improvement, continuously getting better and faster at designing and building successive generations of increasingly powerful machines, creating a runaway effect.
LLM:那么想象一下这些超智能机器吧?他们热衷于 DIY,并且势不可挡!每次他们升级自己时,他们都会变得更快、更强大。今天,它是一个额外的内存条;明天,它是量子处理器。在你意识到之前,他们已经如此领先,以至于我们人类都在吃他们的风扇过滤器灰尘!伙计们,奇点就像类固醇永不停歇的技术升级!
LLM: So imagine these hyper-smart machines, right? They’ve got the DIY bug, and they’re on an unstoppable roll! Each time they upgrade themselves, they get quicker and more powerful. Today, it’s an extra RAM stick; tomorrow, it’s quantum processors. Before you know it, they’re so ahead of the game that they’ve left us humans eating their fan filter dust! The singularity, folks, it’s like a never-ending tech upgrade on steroids!
尽管与某些技术相比,人类对人工智能的不信任似乎更加严重,但在采用和拒绝新技术时,对其用途的抵制、恐惧和误解是一个常见的故事。印刷机、铁路、电力、纺织、制冷、汽车、农业机械、机械化、电视、计算器、自动化、互联网和维基百科,尽管它们被采用并造福于人类,但都面临着一系列的反对。文化。番茄收获机也是如此。
While the mistrust humans have for any AI seem aggrandized compared to some technologies, the resistance, fear, and misunderstanding of its uses are a familiar story when it comes to the adoption and rejection of new technologies. The printing press, the railway, electricity, textiles, refrigeration, the automobile, agricultural machinery, mechanization, television, the calculator, automation, the Internet, and Wikipedia have all faced a spectrum of opposition as much as they have been adopted and benefited human cultures. So have tomato harvesting machines.
法学硕士:二十世纪中叶番茄收割机的引入显着提高了收割效率并改变了农业经济,特别是使加利福尼亚等地区受益。这项创新还导致了更适合机械收获的番茄品种的开发,尽管经常因风味减弱而受到批评。虽然这些机器导致了劳动力市场的变化和一些人的失业,但它们促进了番茄加工行业的增长,并扩大了番茄产品的可用性。这些进步还对环境产生影响,包括化肥和农药使用量的潜在增加以及对水的需求增加。
LLM: The introduction of tomato harvesting machines in the mid-twentieth century significantly increased harvesting efficiency and transformed the agricultural economy, especially benefiting regions like California. This innovation also led to the development of tomato varieties better suited for mechanical harvesting, albeit often criticized for diminished flavor. While these machines led to labor market changes and some displacement, they facilitated the growth of the processed tomato industry and broadened the availability of tomato-based products. These advancements also had environmental implications, including potential increases in fertilizer and pesticide use and greater water demand.
让大家冷静下来,在这个历史时刻和可预见的未来,虽然番茄收获机已成为农业领域公认的技术,但通用人工智能并不存在。也就是说,各种各样的警告表明,在不久的将来,人工智能将被神圣的人类神秘地编程为自主的,在没有讨厌的人类参与的情况下做出决定,展示意识的科学定义,自我决定,从而决定如果人类有必要的话,就需要过滤掉人工智能系统被人类武器化并用于其他不良意图的更周到的警告。与法学硕士的快速交谈揭示了人们对智能机器超越人类创造者智力的恐惧已经存在了多久。
To calm everyone down, at this precise moment in history and for the foreseeable future, while tomato harvesting machines have become accepted technologies in the agricultural landscape, Artificial General Intelligence does not exist. That said, the variety of warnings that suggest a not-too-distant future when AI will mysteriously be programmed by godlike humans to be autonomous, make decisions without pesky humans involved, demonstrate scientific definitions of consciousness, be self-determined, and thus decide if the human race is at all necessary need to be filtered from the more thoughtful warnings of AI systems being weaponized by humans and used for other bad intent. A quick tête-à-tête with an LLM reveals just how long the fear of intelligent machines surpassing the intelligence of their human creators has been around for.
法学硕士:历史上一个值得注意的警告可以追溯到塞缪尔·巴特勒 (Samuel Butler) 1863 年的文章《机器中的达尔文》和后来他 1872 年的小说《Erewhon》,其中推测机器最终会繁殖、进化并超越其人类创造者。这些作品主要是讽刺性和推测性的,但它们确实代表了我们现在所认识的人工智能的一些最早的讨论。
LLM: A notable warning historically dates to Samuel Butler’s 1863 essay “Darwin Among the Machines” and later his 1872 novel “Erewhon,” in which machines are speculated to eventually reproduce, evolve, and surpass their human creators. These works were largely satirical and speculative, but they do represent some of the earliest discussions of what we would now recognize as AI.
进一步的研究表明,塞缪尔·巴特勒 (Samuel Butler) 于 1863 年撰写的《机器中的达尔文》也以雪莱 1818 年关于人类创造超越其创造者的隐喻警告为基础。巴特勒的散文和小说都表明,这种恐惧长期以来一直存在于我们的意识中。 “我们自己正在创造我们自己的继任者,”巴特勒声称,“赋予他们更大的权力,并通过各种巧妙的设计提供自我调节、自我行动的力量,这对他们来说就像智力对人类一样。随着时间的流逝,我们将发现自己是劣等种族。”巴特勒对智能机器的担忧已经传承了一个多世纪。就像今天的现代计算算命师一样,巴特勒针对智能机器做出了以下预测:“现在很复杂,但再过十万年它不会变得更加简单和更容易理解吗?还是两万?关于智能机器警告历史的网络搜索没有提及巴特勒在搜索优化方面的书面工作,而是参考了更现代的资源。它向您表明,与某些已建立的搜索引擎相比,法学硕士也可能导致您的研究中难以找到资源(图1-1)。
Further research reveals that “Darwin Among the Machines” written by Samuel Butler in 1863 also builds on Shelley’s 1818 metaphorical warning about human creations surpassing their creators. Butler’s essay and novel both reveal that this fear has been in our own consciousness for a long time. “We are ourselves creating our own successors,” Butler claimed, “giving them greater power and supplying by all sorts of ingenious contrivances that self-regulating, self-acting power which will be to them what intellect has been to the human race. In the course of ages, we shall find ourselves the inferior race.” Butler’s concerns about intelligent machines have been passed down for over a century. Like today’s modern computational fortune-tellers, Butler made the following prediction referring to an intelligent machine: “Complex now, but how much simpler and more intelligibly organised may it not become in another hundred thousand years? or in twenty thousand?” Web searches on the history of warnings about intelligent machines do not mention Butler’s written work in the search optimization and instead reference more contemporary sources. It goes to show you that an LLM can also lead to difficult-to-locate sources in your research vs. some established search engines (Figure 1-1).
带有链接列表的网络搜索屏幕截图。它们是对媒体网络公司对人类造成致命威胁的历史警告,“人们也问”下建议的搜索查询、哈佛大学和维基百科的文章。
A screenshot of a web search with a list of links. They are the history warns of the deadly threat to humanity from medium dot com, suggested search queries under People also ask, articles from Harvard University and Wikipedia.
对智能机器警告历史的搜索并没有立即揭示其起源,而法学硕士却发现了这一点
A search for the history of warnings about intelligent machines did not immediately reveal its origins, while an LLM did
对计算机科学更相关的历史贡献
More Relevant Historical Contributions to Computer Science
计算机科学还有一段漫长而复杂的历史值得一提。查尔斯·巴贝奇 (Charles Babbage) 和艾达·洛夫莱斯 (Ada Lovelace) 的作品夹在雪莱 1818 年的杰作和塞缪尔·巴特勒 (Samuel Butler) 的警告之间。艾达是一位英国数学家和作家,因其对查尔斯·巴贝奇早期机械通用计算机分析机的研究而闻名。她关于该引擎的笔记包括被认为是第一个由机器处理的算法。正因为如此,她经常被认为是第一位计算机程序员,尽管她的工作比我们现在所认为的现代计算机的发明早了一个多世纪。
There also exists a long and complex history of computer science that is worth mentioning. Sandwiched in between Shelley’s 1818 masterpiece and Samuel Butler’s warning is the work of Charles Babbage and Ada Lovelace. Ada was an English mathematician and writer known for her work on Charles Babbage’s early mechanical general-purpose computer, the Analytical Engine. Her notes on the engine include what is recognized as the first algorithm intended to be processed by a machine. Because of this, she is often regarded as the first computer programmer, even though her work predates the invention of what we now consider a modern computer by over a century.
洛夫莱斯对计算领域的主要贡献是她对分析引擎的潜力的愿景,而不仅仅是计算。在她的笔记中,她想象计算机不仅可以创建数学计算,还可以创建任何形式的内容,例如艺术或音乐,如果提供适当的输入和编程。
Lovelace’s major contribution to the field of computing was her vision of the potential of the Analytical Engine, beyond mere calculation. In her notes, she imagined that a computing machine could create not just mathematical calculations but any form of content, such as art or music, if it were provided with the appropriate input and programming.
正如我的法学硕士很快指出的那样
As my LLM is quick to point out
洛夫莱斯在她的笔记中写道:“分析引擎没有任何自命不凡的能力来创造任何东西。它可以做任何我们知道如何命令它执行的事情。它可以遵循分析,但它没有能力预测任何分析关系或真理”。
Lovelace wrote in her notes, “The Analytical Engine has no pretensions whatever to originate anything. It can do whatever we know how to order it to perform. It can follow analysis, but it has no power of anticipating any analytical relations or truths”.
这是现代计算机设计和使用中的一个关键概念,某种程度上也是人工智能领域的一个关键概念。它强调机器的能力完全由给予它的指令决定,这意味着人工智能和计算机是可以执行任务的工具,但不能像人类意义上的“思考”或“创造”。艾达·洛夫莱斯并没有直接谈论我们今天所知的人工智能,也没有对智能机器超越人类智能发出任何警告。然而,她的想法是计算机科学作为一门学科出现的基础。
This is a critical concept in the design and use of modern computers and, to some extent, in the field of AI. It emphasizes that a machine’s abilities are determined entirely by the instructions given to it, implying that AI and computers are tools that can perform tasks but do not “think” or “create” in the human sense. Ada Lovelace did not directly say anything about AI as we know it today, nor did she make any warnings of intelligent machines surpassing human intelligence. Her ideas, however, were foundational to the emergence of computer science as a discipline.
生成式人工智能通常与通用人工智能联系在一起,重要的是要记住它们是不同的。生成式人工智能与其他狭义人工智能应用程序的不同之处还在于它们被编程执行的任务。不,法学硕士不会被编码来跟踪您出于恶意目的而输入的每个单词。生成式 AI 生成内容(图1-2)。这是他们唯一的任务,但即便如此,他们也并不总是做得那么好。大多数生成式人工智能不存储生成的图像。想象一下数据集会有多大,无法控制。所有生成式人工智能都接受特定数据的训练,除非通过专门的人员参与强化学习,否则这些数据在很大程度上不会增长。但这既耗时又昂贵,并且可能会导致偏差增加。
Generative AI is often associated with AGI, and it’s important to keep in mind that they are different. Generative AI are also different than other narrow AI applications in the tasks they are programmed to perform. No, an LLM is not coded to track every word you input for evil intent. Generative AI generate content (Figure 1-2). That is their sole task, and even then, they don’t always do that well. Most generative AI don’t store the images that are generated. Imagine how uncontrollably large the data set would be. All generative AI are trained on specific data that for the most part does not grow unless through dedicated humans involved in reinforcement learning. But that’s time-consuming and expensive and may lead to an increase in bias.
AI生成的城市鸟瞰蓝图照片。建筑结构按结构化布局排列。
A photograph of the blueprint of the aerial view of a city generated by A I. The building structures are arranged in structured layouts.
文本图像人工智能生成的几张图像的蓝图显示出复杂性和细节,但无意统治人类世界
A blueprint of several generated images by a text-image AI shows intricacy and detail but no desire to rule the world of humans
虽然生成式人工智能可以提出有偏见和不真实的内容,并排除不遵循规范的声音,但其他分析大量数据并做出预测的狭义人工智能应用程序可能会导致隐私、监视和歧视等问题。这些人工智能通常由缺乏透明度和问责制的公共或私人实体控制,特别是当影响人类生活的关键决策是由机器做出时。当许多人工智能编程系统变得如此自动化,以至于变得有些隐形时,人们很容易很快就认为人工智能正在接管,因为它们继续扰乱我们习惯做事的方式,这是理所当然的。既然生成式人工智能已经渗透到公司和教育机构中,我们至少不再对这项技术带来的力量和潜力熟视无睹:好的、坏的或介于两者之间。区分生成式人工智能好坏的一个重要因素取决于影响其生成内容的人以及他们这样做的动机。
While generative AI can propose content that is biased and untrue and exclude voices that don’t follow the norm, other narrow AI applications that analyze large amounts of data and make predictions can lead to issues like privacy, surveillance, and discrimination. These AI are often controlled by public or private entities that lack transparency and accountability particularly when critical decisions affecting the lives of humans are made by machines. It’s also easy to form a quick opinion that the AI are taking over when many artificially intelligent programmed systems are so automated as to have become somewhat invisible, taken for granted as they continue to disrupt the way we are used to doing things. Now that generative AI has infiltrated companies and educational institutions, we are at least no longer asleep to the power and potential that comes with the technology: good, bad, or somewhere in between. An important factor that differentiates whether generative AI is good or bad is dependent on the human who influences what it will generate and their motivation for doing so.
科技很糟糕……人工智能很糟糕
Tech Is Bad… AI Is Bad
每种技术都容易以不当、破坏性且常常是暴力的方式使用。有时,技术被用来强化现状,排除社会认为“正常”范围之外的声音,或者使虚假信息或谎言永久化。那些开发技术的人不能再依靠指责他们共同创造的幼儿来免除他们任何责任的论据。技术,任何技术,都不是中立的力量。它可以用于好的方面,也可以用于坏的方面,并且可以介于两者之间。当我们检查生成式人工智能的极端案例时,这一点就很明显了,这些案例已经出现在滥用机器学习模型来生成深度伪造品的过程中,特别是那些未经名人许可而在其他人身上使用名人面孔来生成赚钱内容、伪造品的情况。新闻和色情内容。
Every technology is prone to be used in inappropriate, damaging, and often violent ways. At times technologies are used to reinforce status quo, exclude voices that fall outside what a society considers “normal,” or perpetuate false information or untruths. Those that develop the technologies can no longer rely on arguments that absolve them of any responsibility by blaming the toddler that they co-created. Technology, any technology, is not a neutral force. It can be used for good and for bad and on a spectrum between. This is evident when we examine extreme cases of generative AI that have already surfaced in the abuse of machine learning models to generate deep fakes and in particular those that use the faces of celebrities on other bodies without their permission to generate money-making content, fake news and pornography.
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支持一些预可视化任务,例如快速生成概念艺术以获取有关角色或环境的外观和感觉的反馈。此功能使创意人员能够更快地找到并填充他们正在处理或想要向其他人推销的项目的情绪板。
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Supporting some pre-visualization tasks like generating concept art quickly to get feedback on the look and feel of a character or environment. This feature allows creatives to more rapidly locate and populate a mood board for a project they are working on or want to pitch to others.
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替换图像中的背景,使创意人员有机会快速查看他们拍摄的照片中的主题在多种类型的背景中的外观。这一功能现在在 Photoshop 等流行软件中可用,可以自动完成某些情况下长达数小时的工作。
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Replacing background in images, giving creatives the opportunity to see what a subject they captured as a photo might look like in multiple types of backgrounds quickly. This feature, now available in popular software like Photoshop, automates what amounts to many hours of work in some cases.
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动态描画是动画师用来逐帧追踪电影素材(一秒 24 帧)的技术,可以减轻以前繁琐的工作并加快流程。
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Rotoscoping, a technique used by animators to trace over motion picture footage frame by frame (that’s 24 frames in one second) that relieves previous tedious work and accelerates the process.
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将分辨率从 2K 提高到 4K,让动画师以较低的分辨率创作作品,然后允许 AI 将其升级到更高的分辨率。此过程节省了渲染时间和金钱。
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Increasing resolution from 2K to 4K, letting animators create work in lower resolutions and then allowing the AI to upscale them to higher resolutions. This process saves time and money for rendering.
生成式人工智能促使我们质疑它在我们自己的创作过程中的作用,并让我们将我们承担的那些任务定义为创造性任务和那些较少的任务。生成式人工智能技术最适合用于支持那些创意人员认为创意较少的任务,并且当创意人员可以专注于根据客户、团队或用户反馈对其正在进行的工作进行更改时,可以节省有用的时间。生成式人工智能具有创造力以及创造力本身可以与智力相关的幻想是一种概括,没有证据支持的研究或人工智能跨创意产业的务实整合的支持。例如,人工智能接管艺术家工作的争论可能会平息,就像生成式人工智能被编程为寻找模式并从这些模式生成内容一样,许多艺术家寻找模式是为了打破它们,超越它们他们创造出一些以前从未创造过的东西。人工智能作为一项技术的突破性部分并不在于代码本身,而在于引导其支持独特的创造行为的创意想象力。
Generative AI provoke us to question its role within our own creative process and that we define those tasks we undertake as creative and those that are less. The technology of generative AI is best applied in supporting those tasks that creatives deem less creative and can be a useful time saver when a creative can focus on making changes to their works in progress based on client, team, or user feedback. The illusion of generative AI being creative and that creativity itself can be correlated to intelligence is a generalization that is not supported by evidence-backed research nor by the pragmatic integration of AI across creative industries. What may mute debates of an AI taking over the job of an artist, for example, is that just as generative AI are programmed to seek patterns and generate content from those patterns, many artists look for patterns in order to break them, to move beyond them to create something that has not been created before. The ground-breaking part of AI as a technology is not in the code itself, but lies in the imagination of the creative that guides it to support unique acts of creation.
技术很好……人工智能很好
Tech Is Good… AI Is Good
人工智能生成的鸡的照片。左边的鸡有一只眼睛,中间的鸡头上有两个王冠,右边的鸡身材矮小,有一个长喙。
A photograph of the A I generated chickens. The left chicken has one eye, the middle chicken has two crowns on his head, and the right chicken is short and has a long beak.
提示“鸡对天塌下来的反应”伴随着一张来自鸡档案片段的原始照片。应用了使眼睛变得巨大的风格过滤器。总迭代次数 = 20
The prompt “chickens reacting to the sky falling” accompanied an original photo from archive footage of chickens. A style filter that makes eyes giant was applied. Total iterations = 20
因此,让我们将其付诸实践,通过重塑钱德勒在人工智能吸引越来越多人类注意力的历史时期的著名故事来纪念他。
So let’s put that to practice, honoring Chandler by reinventing his well-known story for a time in history where AI is captivating the attention of an increasing number of humans.
作者:给我一个小鸡故事的版本:“天塌下来了。天塌下来了”,但使用人工智能。
Author: Give me a version of Chicken Little’s story with “The sky is falling. The sky is falling” but use AI.
LLM :从前,在一个小村庄里,住着一只名叫小鸡的鸡。有一天,利特尔在地上啄食时,听到一种奇怪的声音。突然,一架人工智能气象无人机飞过头顶,投射出黑暗、暴风雨天空的全息图像。无人机宣布:“天塌下来了!天塌下来了! (图 1-4)”
LLM: Once upon a time, in a small village, there lived a chicken named Little. One day, while pecking at the ground for food, Little heard a strange noise. Suddenly, an AI-powered weather drone flew overhead and projected a holographic image of a dark, stormy sky. The drone announced, “The sky is falling! The sky is falling! (Figure 1-4)”
一张人工智能生成的谷仓夜间照片。谷仓周围都是母鸡。两架无人机在谷仓上空盘旋。背景中有一片森林。
A photograph of an A I generated barn at night. The barn is surrounded by hens. Two drones are hovering above the barn. There is a forest in the background.
提示“现代农场里的动画鸡,暴风雨的天空,无人机投射的云层后面有一些阳光,树木,4K”伴随着我姐姐 30 年前拍摄的一张有鸡的农场的照片。迭代次数 = 61
The prompt “animated chickens on a modern farm, stormy sky with some sun behind clouds projected by a robot drone, trees, 4K” accompanied a photo of a farm with chickens taken by my sister 30 years ago. Iterations = 61
小小很害怕,跑去告诉村里的其他动物。他们都嘲笑她,认为这只是她又一个疯狂的想法。但利特尔决心警告他们危险并着手寻找解决方案。
Little was terrified and ran to tell the other animals in the village. They all scoffed at her, thinking it was just another one of her wild ideas. But Little was determined to warn them of the danger and set out to find a solution.
她遇到了一群正在研究人工智能天气预报系统的科学家(图 1-5)。他们向她解释说,人工智能检测到风暴即将来临,村庄需要为此做好准备。小小闻言松了口气,跑回村里告诉其他人这个好消息。
She came across a group of scientists who were working on an AI-powered weather forecasting system (Figure 1-5). They explained to her that the AI had detected an approaching storm and that the village needed to prepare for it. Little was relieved to hear this and ran back to the village to tell the others the good news.
一张人工智能生成的卡通照片,描绘了 5 只狐狸在笔记本电脑上工作。其中一只狐狸正在调整笔记本电脑顶部的天线。狐狸有双重色调。
A photograph of an A I generated cartoon depicting 5 foxes working on a laptop. One of the foxes is adjusting the antenna on the top of the laptop. The foxes are in double shades.
提示“一群 2D 动画狐狸正在研究人工智能天气预报系统”,基于 archive.org 上存档的 1908 年插图封面,更换了狐狸后面和笔记本电脑屏幕上的背景,进行了色彩校正,使狐狸的颜色更加鲜艳橙子。总迭代次数 = 46
The prompt “a group of 2D animated foxes working on an AI-powered weather forecasting system” based on an archived 1908 illustration cover found on archive.org, with background replaced behind foxes and on the laptop screen, color correction to make fox colors more orange. Total iterations = 46
A photograph of the A I generated chickens. The chicken on the left is short and has large eyes, the chicken in the middle has large cheeks, and the chicken on the right is grey and short. A bolt of lightning strikes in the distance.
A photograph of the A I generated chickens. The chicken on the left is short and has large eyes, the chicken in the middle has large cheeks, and the chicken on the right is grey and short. A bolt of lightning strikes in the distance.
从那天起,利特尔因其敏捷的思维和愿意相信人工智能的力量而被称为村里的英雄。这个村庄学会了信任人工智能天气预报系统,它帮助他们免受未来风暴的影响。
From that day on, Little was known as the village’s hero for her quick thinking and her willingness to believe in the power of AI. And the village learned to trust in the AI-powered weather forecasting system, and it helped them keep safe from future storms.
结束。
The end.
就讲故事而言,法学硕士提供的一个有趣的转折需要精心设计,但种子已经存在。我们有一架人工智能驱动的无人机,它似乎在自行行动并引起恐慌,后来才发现它是由科学家操作的,以警告小鸡和她的朋友前方的危险。人工智能显示了人类(或在本例中为狐狸)和人工智能内在的相互依赖性。对于那些熟悉《小鸡小鸡》故事的人来说,生成的版本在深度、寓言或丰富的人物塑造方面确实与原作相差甚远。然而,它可能成为新故事的种子。生成的故事还揭示了法学硕士必须包含在故事中的意外吹嘘。这种哗众取宠的行为也表明了绿野仙踪在幕后的表现,以及他们需要吹嘘他们的弗兰肯蹒跚学步的人。
An interesting twist offered up by an LLM needs crafting as far as storytelling goes, but the seeds are there. We have an AI-powered drone seemingly acting on its own and creating panic only to find out later that it is being operated by scientists to warn Chicken Little and her friends of the danger ahead. The AI shows the intrinsic interdependency of human (or in this case fox) and AI. For those familiar with the story of Chicken Little, the generated version really does not even come close to the original in depth, allegory, or rich characterization. It might, however, become the seed for a new story. The generated story also reveals the unexpected bragging that the LLM had to include as part of the story. That grandstanding is also an indicator of the Wizard of Oz behind the curtain and their need to boast about their Frankentoddler.
任何类型的生成故事都可以由任何创意人员策划,并且当不将其视为最终产品而是将其视为创意和关键流程的一部分时,可以更合乎道德地使用。各种各样的原型都成为可能,可以激发各种创作者的灵感。使用小鸡故事中的情节点和角色生成有关人工智能的故事的活动向我们展示了一个需要完善的原型。显而易见,生成式人工智能除了精炼人工智能生成的内容之外,还需要人类参与其中才能生成任何东西。每一个狭隘的人工智能都需要人类参与其中。需要引导他们有意图和目的。他们无法独自做到这一点。
Generated stories of all types can be curated by any creative and can be used more ethically when thought of not as an end product, but as part of your creative and critical process. All manner of prototypes are made possible that can inspire creators of all kinds. The activity of generating a story about AI using plot points and characters that were part of the Chicken Little story showed us a prototype that needs refinement. Stating the obvious, generative AI needs the human in the equation in order to generate anything, in addition to refining content that an AI generates. Every narrow AI requires the human in the equation. They need to be guided to have intention and purpose. They are unable to do that on their own.
调和人工智能的炒作与诽谤
Reconciling the Hype and the Vilification of AI
作为不断寻找新工具的创意人员,在使用生成式人工智能之前协调其使用非常重要。人工智能并不是第一个引起我们广泛关注的技术。我们对任何技术的正面和负面炒作的反应都是一种历史模式,作者兰登·温纳 (Langdon Winner) 在他1988 年出版的《鲸鱼和反应堆》一书中很好地阐述了这一点。对于温纳和他的书出版前后的许多思想家来说,对于正在采用的任何技术的社会、经济和政治层面,保持清醒和批判性的积极态度至关重要。人类与可编程机器的互动不断引发媒体对其利弊进行权衡,通过夸张夸张、不合理的恐惧和消极情绪夸大人工智能(AI)来争夺人们的注意力。您将阅读或聆听并观察正面和负面的头条新闻,包括那些基于网络的法学硕士,它们可以生成任何内容,从一篇关于艾伦图灵的影响的文章(省略了琼克拉克)到对一位作者写一本关于生成人工智能的书的极其不准确的描述在图书馆里。受欢迎的作家、思想家、政治家、科学家、艺术家和活动家进一步放大了观点。接下来引人注目的头条新闻是使用应用监督和强化学习方法的法学硕士生成的。作为您自己的创意过程的一部分,请让法学硕士研究人工智能的优点和缺点。您会发现,负面和正面的标题在被视为真相陈述之前都需要严格的关注和研究。人类生成的头条新闻也是如此。使用生成式人工智能的决定需要您自己的洞察力。
As a creative on the constant lookout for new tools, it’s important to reconcile your use of generative AI prior to using it. AI is not the first technology to gather our critical attention. Our reactions to the positive and negative hype of any technology are a historical pattern that was well articulated by author Langdon Winner in his book The Whale and the Reactor, published in 1988. For Winner and many thinkers before and after his book was published, it is crucial to be awake and critically active regarding the social, economic, and political dimensions of any technology that is in the process of being adopted. Human interactions with programmable machines have persistently triggered media outlets to weigh in on their pros and cons, to compete for your attention by dramatizing artificial intelligence (AI) with a mix of exaggerated hyperbole and unreasonable fear and negativity. You’ll read or listen to and observe positive and negative headlines including those web-based LLMs that can generate anything from an essay on the influence of Alan Turing that omits Joan Clarke to a ridiculously inaccurate depiction of an author writing a book on generative AI in a library. Opinions are further amplified by popular authors, thinkers, politicians, scientists, artists, and activists. The attention-grabbing headlines that follow were generated using an LLM that applied supervised and reinforcement learning methods. As part of your own creative process, task an LLM to generate the pros and cons of AI. You will see that both negative and positive headlines require critical attention and research prior to being taken for truth statements. The same can be said of human-generated headlines. The decision to use generative AI requires your own discernment.
积极的头条新闻
Positive Headlines
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“人工智能为企业带来显着的生产力提升”
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“AI leads to significant productivity gains for businesses”
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“人工智能驱动的医疗保健系统可改善患者的治疗结果”
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“AI-powered healthcare systems improve patient outcomes”
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“人工智能通过更有效地利用能源来帮助应对气候变化”
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“AI helps tackle climate change through more efficient energy use”
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“人工智能驱动的教育彻底改变了学习体验”
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“AI-powered education revolutionizes the learning experience”
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“人工智能在技术和数据领域创造新的就业机会”
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“AI creates new job opportunities in technology and data fields”
负面头条新闻
Negative Headlines
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“人工智能系统会延续并放大偏见和歧视”
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“AI systems perpetuate and amplify bias and discrimination”
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“人工智能导致传统行业失业”
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“AI leads to job loss and unemployment in traditional industries”
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“人工智能引发了监控和决策中的道德和隐私问题”
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“AI raises ethical and privacy concerns in surveillance and decision-making”
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“人工智能在人类不知情的情况下窃取了人类的工作成果”
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“AI steals the work of humans without them even knowing”
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“人工智能通过自动化高薪工作加剧了收入不平等”
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“AI exacerbates income inequality through automating high-paying jobs”
人为生成的头条新闻
Human-Generated Headlines
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人工智能就像原子弹的制造(沃伦·巴菲特)
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AI is like the creation of the atom bomb (Warren Buffet)
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人工智能机器不会产生“幻觉”。但他们的制造者是(娜奥米·克莱因)
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AI machines aren’t “hallucinating.” But their makers are (Naomi Klein)
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“人工智能教父”表示他担心“人类的终结”(指杰弗里·辛顿)
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The “godfather of AI” says he’s worried about “the end of people” (referring to Geoffrey Hinton)
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“我们有点害怕”:OpenAI CEO警告人工智能风险
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“We are a little bit scared”: OpenAI CEO warns of risks of artificial intelligence
人工智能真的像原子弹的制造一样吗?这需要研究,但这种夸张的夸张背后可能有其他意图。也就是说,如果人工智能被编程来玩战争游戏,而一个虚无主义的程序员决定让它控制真正的核弹,那么,是的,人工智能和原子弹一样危险。人类创造的人工智能的崛起是否标志着“人类的终结”,或者是人工智能的悲剧英雄所做出的声明,他感到有必要为自己在人工智能发展中所扮演的角色道歉,尽管早在很早之前就已经存在了早期警告1863?人工智能与人类末日未来之间的相关性取决于人类赋予人工智能的决定权。这种情况并不意味着人工智能需要有感知能力。这意味着对人工智能可以实现的自动化的更大控制需要关注和监管。
Is artificial intelligence really like the creation of the atom bomb? That requires research, but likely the exaggerated hyperbole has other intentions behind it. That said, if an AI is programmed to play out war games and a nihilistic programmer decides to let it control real nuclear bombs, then, yes, AI is as dangerous as an atom bomb. Does the rise of human-created artificial intelligence signal the “end of people,” or is that statement generated by a tragic hero of AI who feels compelled to apologize for their role in its development, even though there already existed earlier warnings as early as 1863? The correlation between AI and any apocalyptic future for humanity is dependent on what deciding powers humans give any AI. That scenario does not mean an AI needs to be sentient. It means that greater control over what any AI can automate needs attention and regulation.
无论是否遵循每一个需要人为干预来终结人类的场景,受欢迎的法学硕士都将继续引起人们的注意,因为它们被编程为生成规范内容并以规定的方式模拟类人的交流。他们似乎能够回答我们用人类语言向他们提出的问题或提示。他们使用传统的方式来交流我们熟悉的想法。然而,尽管程序员不断地采取各种方法让它们看起来更人性化,但我们也需要有洞察力,将它们与我们自己的社交和对话关系与生活中真实的人类进行比较。我们同样会对法学硕士从其庞大的数据集中获得的知识感到敬畏,就像我们对它排除不属于常态的声音感到惊讶一样。当周围没有人可以与你进行创造性的对话,并且有意地专注于你正在思考的创造性想法时,生成式人工智能可能只是在那一刻有用的伴侣或缪斯。
Regardless of following through on each scenario requiring human intervention in order to end the human race, popular LLMs will continue to raise furtive eyebrows because of being programmed to generate normative content and to emulate human-like communication in a prescriptive way. They seem capable of answering questions or prompts that we throw at them using human-speak. They use conventional ways to communicate ideas that we are familiar with. Yet, despite ongoing methods by programmers to make them appear more human, we also require the discernment to compare them to our own social and conversational relationships with the real humans in our lives. We can equally be in awe with the knowledge an LLM can regurgitate from its large data set, as we can be astonished by its exclusion of voices who are not part of the norm. When there is no one around to have a creative conversation with that is intentionally focused on a creative idea you are thinking about, generative AI may just be a useful companion or muse in that moment.
天网蓬勃发展时可尝试的创意活动
Creative Activities to Try While Skynet Thrives
原子弹、人类末日以及对人工智能的恐惧都是用来谈论人工智能危险的隐喻。它们也可以成为创意温室。您可以使用这些故事、隐喻和警示故事作为您自己的科幻小说、歌曲、设计、漫画、网站、TikTok 短片、电视剧或博客文章的起点。
The atom bomb, the end of people, and being frightened with AI are all metaphors that are used to talk about the dangers of AI. They can also be creative hothouses. You can use these stories, metaphors, and cautionary tales as jumping-off points for your own science fiction, song, designs, manga, website, TikTok short, TV series, or blog post.
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巴勃罗·毕加索的《格尔尼卡》是为了回应西班牙内战期间格尔尼卡的轰炸而创作的。这幅画赤裸裸地描绘了战争的混乱和暴力,使其成为我所经历过的最有力的反战声明之一。
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Pablo Picasso’s Guernica was created in response to the bombing of Guernica during the Spanish Civil War. The painting is a stark portrayal of the chaos and violence of war, making it one of the most powerful anti-war statements I have ever experienced.
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墨西哥画家弗里达·卡罗(Frida Kahlo)用她的艺术来表达她在一场严重的交通事故后所遭受的身体和情感上的痛苦,这场事故使她卧床不起,一生都在痛苦中。她的作品对痛苦的原始描绘常常令人震惊,却成为力量和韧性的象征。
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Mexican painter Frida Kahlo used her art to express her physical and emotional suffering following a severe traffic accident that left her bedridden and in pain for much of her life. Her work, often shocking in its raw portrayal of pain, became a symbol of strength and resilience.
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在被判处死刑并在最后一刻减刑后,作家陀思妥耶夫斯基继续创作了《罪与罚》、《卡拉马佐夫兄弟》和《地下笔记》等重要小说。
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After being sentenced to death and then having the sentence commuted at the last minute, writer Fyodor Dostoevsky went on to write important novels like Crime and Punishment, The Brothers Karamazov, and Notes from Underground.
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美国诗人、作家和民权活动家玛雅·安吉卢(Maya Angelou)童年时期经历了种族歧视和性虐待的创伤,她将这些经历诗意地融入到她的写作中,包括她的自传体作品《我知道笼中鸟为何歌唱》。
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American poet, writer, and civil rights activist Maya Angelou faced a traumatic childhood with racial discrimination and sexual abuse that she channeled poetically into her writing, including her autobiographical work, I Know Why the Caged Bird Sings.
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作为抗议场所,匿名街头艺术家班克斯用他们的作品来评论政治和社会问题,如战争、资本主义和贫困。值得注意的是班克斯的《气球女孩》,它在 2018 年 10 月伦敦苏富比拍卖会上自我粉碎,当时木槌敲下,确认了超过 100 万英镑的最终出价。该作品后来更名为《爱在垃圾桶里》,是对艺术界及其商业化实践的直接批评。
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Ever the site of protest, the anonymous street artist Banksy uses their work to comment on political and societal issues, such as war, capitalism, and poverty. Notable is Banksy’s Girl with Balloon, which self-shredded during a Sotheby’s auction in London in October 2018, just as the gavel came down to confirm the final bid of over £1 million. The work was later renamed Love Is in the Bin and was a direct critique of the art world and its commercialization practices.
还有更多的艺术家将他们所处时代的逆境和挑战转化为强大的创意表达,这表明艺术和创意行为可以成为处理和交流困难经历以及批评既定社会实践和行为的深刻工具。所有学科的创意人员已经开始利用生成式人工智能作为社会批评的焦点。 Trevor Paglen 以人工智能和监控领域的工作而闻名,他利用人工智能和机器学习创建了一系列名为“机器视觉”的图像。该项目旨在批评和提出有关人工智能系统如何“训练”以观察和解释世界的问题。 Holly Herndon、Taryn Southern、Dadabots、Ash Koosha 等音乐艺术家强调了人工智能作为创意工具的潜力,并提出了关于作者身份、创造力以及日益自动化的世界中音乐的未来的重要问题。
There are many more artists who have transformed their adversity and the challenges of their time into powerful creative expressions, showing that art and creative acts can be a profound vehicle for processing and communicating difficult experiences and critiquing established social practices and behaviors. Creatives of all disciplines are already engaged in leveraging generative AI as a place of focus for social critique. Trevor Paglen, known for his work with AI and surveillance, used AI and machine learning to create a series of images titled “Machine Visions.” The project was designed to critique and raise questions about how AI systems are “trained” to see and interpret the world. Musical artists like Holly Herndon, Taryn Southern, Dadabots, Ash Koosha, and others highlight the potential of AI as a creative tool and also raise important questions about authorship, creativity, and the future of music in an increasingly automated world.
五个为什么
Five Why’s
您还可以应用创意人士使用的设计工具来找到问题的根源。 “五个为什么”练习不断地询问团队试图识别的特定问题的原因。询问我们的法学硕士是否熟悉设计思维活动会得到以下答复。
You can also apply a design tool that creatives have used to get to the root of a problem. The Five Why’s exercise continuously asks why to a particular problem that a team is trying to identify. Asking our LLM if it is familiar with the design thinking activity generates the following response.
LLM:“五个为什么”是一种解决问题的工具,可以鼓励人们更深入地了解当前的问题。最初由丰田佐吉开发,并在丰田汽车公司制造方法的演变过程中使用,现在已应用于各个行业。这个过程涉及反复询问“为什么?”揭开问题的各个层面并找到根本原因。识别出最初的问题后,您会问:“为什么这是一个问题?”这个问题的答案就成为下一个“为什么?”的基础。问题等等。这一直持续到你问“为什么?”五次或直到弄清楚问题的根本原因是什么。
LLM: The Five Why’s is a problem-solving tool that encourages a deeper understanding of the issue at hand. Originally developed by Sakichi Toyoda and used within the Toyota Motor Corporation during the evolution of its manufacturing methodologies, it’s now used in various industries. The process involves repeatedly asking “Why?” to peel back the layers of an issue and get to the root cause. After an initial problem is identified, you ask, “Why is this a problem?” The answer to that question then becomes the basis for the next “Why?” question and so forth. This continues until you’ve asked “Why?” five times or until it’s clear what the root cause of the problem is.
如果担心人工智能在各方面变得像人类并最终取代人类,你可以质疑这个假设本身。从“为什么”这个词开始,生成你自己的线索,或者更好的是,构建五个为什么的活动,让法学硕士来回答。
In the case of the fear of AI becoming human-like in every way and eventually dispensing of humans, you can interrogate the assumption itself. Start with the word “Why” and generate your own thread or, better yet, structure the Five Why’s activity for an LLM to answer.
作者:将五个为什么应用于以下陈述:人类担心人工智能会变得有意识并且不再需要它们。
Author: Apply the Five Why’s to the following statement: humans fear that AI will become conscious and no longer need them.
LLM:当然,让我们将五个为什么应用于该陈述。
LLM: Absolutely, let’s apply the Five Why’s to that statement.
为什么人类担心人工智能会变得有意识而不再需要它们?
Why do humans fear that AI will become conscious and no longer need them?
因为他们担心失去对人工智能的控制,这可能会导致潜在的伤害或人类角色的取代。
Because they worry about losing control over AI, which might lead to potential harm or displacement of human roles.
为什么人类担心失去对人工智能的控制?
Why do humans worry about losing control over AI?
因为人工智能系统如果有意识和自主,可能会做出不符合人类利益或道德标准的决策。
Because AI systems, if conscious and autonomous, might make decisions that are not aligned with human interests or ethical standards.
为什么人工智能系统会做出不符合人类利益或道德标准的决策?
Why might AI systems make decisions that are not aligned with human interests or ethical standards?
因为人工智能,特别是如果它实现了意识,会根据其编程而行动,而不一定是人类的道德或情感。如果它没有经过适当的编程来考虑这些因素,它可能会做出对人类有害或令人不安的决定。
Because AI, especially if it achieved consciousness, would act based on its programming and not necessarily human ethics or emotions. If it’s not properly programmed to consider these factors, it may make decisions that are harmful or unsettling to humans.
为什么人工智能不能被适当地编程来考虑人类的道德和情感?
Why may AI not be properly programmed to consider human ethics and emotions?
因为即使开发人员努力将道德考虑嵌入到人工智能中,捕捉人类道德和情感的复杂性和细微差别仍然极具挑战性。此外,全球对某些道德标准缺乏共识。
Because even though developers strive to embed ethical considerations into AI, it’s extremely challenging to capture the complexity and nuances of human ethics and emotions. Also, there’s a lack of global consensus on certain ethical standards.
为什么在人工智能编程中捕捉人类道德和情感的复杂性和细微差别具有挑战性?
Why is it challenging to capture the complexity and nuances of human ethics and emotions in AI programming?
因为人类的道德和情感非常复杂、依赖于具体情况,而且往往是主观的。它们已经进化了数千年,并受到文化、个人和情境因素的影响,这些因素很难全面编码到人工智能系统中。
Because human ethics and emotions are deeply complex, context-dependent, and often subjective. They have evolved over thousands of years and are influenced by cultural, personal, and situational factors that are difficult to comprehensively codify into an AI system.
您可以应用自己的提示或创建“人类担心人工智能会变得有意识并且不再需要它们”的变体,或者简单地重新生成提示并查看人工智能是否给您另一个响应。
You can apply your own prompt or create a variation of “humans fear that AI will become conscious and no longer need them,” or simply regenerate the prompt and see if the AI gives you another response.
当你应用“五个为什么”来促使法学硕士做出回应时,即使是对 AGI 毫无根据的恐惧也可以转变为创造性的目的。在此过程中,您可能会发现“五个为什么”与生成式人工智能相结合可以产生一些您可以询问的有趣的根本原因问题,并且该活动可以应用于其他设计问题。
As you apply the Five Why’s to prompt a response from an LLM, even an unfounded fear of AGI can be turned around for creative purposes. In doing so you might discover that the Five Why’s combined with a generative AI can yield several interesting root cause problems you can interrogate, and the activity can be applied to other design problems.
作为创意人员,面对生成式人工智能的相互冲突的情绪反应是很重要的。艺术家们坚持批判性地对待技术,并将这种批评融入到他们的创造性表达中。作为一个有创造力的人,你不会遵循危言耸听或夸张的模式,而是会从发展自己使用生成人工智能的理由中受益。您可能会认为,过去两个世纪艺术家和设计师的大部分目的都是为了打破惯例、破坏社会礼仪和拆除既定形式。虽然有些创意人员是为了钱,但你可能不会仅仅因为它们被证明是成功的而对重复以前的模式感兴趣。想想那些打破了在自己的学科(如视频游戏、音乐或视觉艺术、舞蹈、戏剧或电影)中展示自己创作的模式的创意人员。他们的共同点是反复尝试破坏观众的期望。您如何整合生成式人工智能来颠覆您自己既定的创造模式?生成式人工智能如何支持您自己的创作过程的发展?为什么您觉得有必要这样做?
As creatives, the conflicting emotional reactions to generative AI are important to face. Artists have persistently taken on technology critically and integrated that criticism into their creative expression. Rather than following the pattern of fearmongering or hyperbole, as a creative person you will benefit from developing your own rationale for using generative AI. You might consider that much of the purpose of artists and designers in the last two centuries has been about breaking convention, disrupting social etiquettes, and dismantling established forms. While some creatives are in it for the money, you may not be as interested in repeating patterns of what came before simply because they proved successful. Consider those creatives that have broken patterns of presenting their creations within their own disciplines like video games, music or visual art, dance, theater, or film. What they share in common are their iterative attempts to disrupt an audience’s expectations. How might you integrate generative AI to disrupt your own established patterns of creation? How might generative AI support your own creative process to evolve? Why might you feel a need to do so?
A photograph of an A I generated image depicts robotic hands grasping a hollow globe of Earth. A small robot is placed on the globe. Tiny planets are scattered around the globe.
A photograph of an A I generated image depicts robotic hands grasping a hollow globe of Earth. A small robot is placed on the globe. Tiny planets are scattered around the globe.
图像-图像AI中包含提示“人工智能手中的虚拟世界”,以及作者手里拿着地球仪的旧图像。作者的身体被裁剪掉,两种风格的过滤器链提示了 78 次迭代,应用了时尚、玩具和布料过滤器
The prompt “A virtual world in the hands of an AI” was included in an image-image AI along with an old image of the author holding a globe of the earth in his hand. The author’s body was cropped out, and two style filters chain prompted 78 iterations with fashion, toy, and cloth filters applied
致谢
Acknowledgments
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约翰·格林·钱德勒 (John Greene Chandler) 创作了令人难忘且至今仍具有现实意义的《小鸡的非凡故事》
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John Greene Chandler for the memorable and still relevant Remarkable Story of Chicken Little
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任何曾经绘制、绘画或 3D 建模机器人、狐狸、鸡和地球的人
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Anyone who has ever drawn, painted, or 3D modeled robots, foxes and chickens, and the earth
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任何创造过草地、天空和其他自然物体的人
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Anyone who has created grass, skies, and other natural objects
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为我们提供 ChatGPT-4 等创意原型的团队
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The teams who have offered us the creative prototypes like ChatGPT-4
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卡莱斯图斯·朱马 (Calestous Juma) 撰写了令人振奋的著作《创新及其敌人:人们为何抵制新技术》
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Calestous Juma for his invigorating book Innovation and Its Enemies: Why People Resist New Technologies
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世界各地的艺术家通过艺术、设计和恶作剧勇敢地挑战人类对待彼此、地球和自己的方式
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Artists everywhere who have bravely challenged the way that humans do things to each other, the planet, and themselves through art, design, and mischief
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毕加索、卡罗、陀思妥耶夫斯基、安杰卢、班克斯
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Picasso, Kahlo, Dostoevsky, Angelou, Banksy
参考
References
巴特勒,S.(1863)。 “机器中的达尔文”,205。
Butler, S. (1863). “Darwin Among the Machines,” 205.
钱德勒,JG (1855)。小鸡的非凡故事。 WJ 雷诺兹公司,康希尔 24 号。
Chandler, J. G. (1855). Remarkable Story of Chicken Little. W. J. Reynolds & Company, 24 Cornhill.
洛夫莱斯,AA (1843)。译者注释(对 LF Menabrea 的“查尔斯·巴贝奇发明的分析机的草图”的翻译的附录)。科学回忆录,选自《外国科学院学报》和《外国期刊》,3, 691–731。
Lovelace, A. A. (1843). Notes by the translator (addenda to her translation of LF Menabrea’s “Sketch of the Analytical Engine Invented by Charles Babbage”). Scientific Memoirs, Selected from the Transactions of Foreign Academies of Science and Learned Societies, and from Foreign Journals, 3, 691–731.
温纳,L. (2010)。鲸鱼和反应堆:在高科技时代寻找极限。芝加哥大学出版社。
Winner, L. (2010). The Whale and the Reactor: A Search for Limits in an Age of High Technology. University of Chicago Press.